Senior Network Software Validation Engineer – AI Clusters

Requirements:

• B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or related technical field, or equivalent practical experience.
• 8+ years of hands-on experience in networking, system validation, software testing, or system-level debugging on Linux.
• Strong Linux systems knowledge and networking debugging experience in scale.
• Proven experience debugging complex production systems by forming hypotheses, designing experiments, and driving issues to root cause.
• Ability to read and reason about source code and collaborate closely with development teams to validate fixes.
• Strong scripting and automation experience using Python, Bash, and/or Ansible.
• Excellent analytical, troubleshooting, communication, and collaboration skills with a strong sense of ownership.
• Fast learner with curiosity for AI infrastructure, distributed systems, and modern AI-assisted engineering tools.

What You'll be Doing:

• Design validation methodologies, review product requirements, and develop comprehensive test plans for networking technologies in large-scale AI cluster solutions.
• Develop and maintain automation tools and scripts for test execution, environment setup, log collection, and data analysis.
• Execute functional, regression, performance, scale, and reliability testing across networking and AI cluster solutions.
• Own end-to-end investigation of complex customer issues by reproducing real-world scenarios, analyzing logs, telemetry, packet captures, and system metrics.
• Read and understand source code (C/C++/Python) to investigate defects, validate fixes, and improve logging, instrumentation, and debugging capabilities.
• Collaborate closely with software and hardware development teams to debug networking technologies, including NCCL, RoCE, RDMA, and related software components.
• Profile and benchmark AI training and inference workloads, correlating application behavior with network and system telemetry to identify scalability and performance limitations.
• Document findings, communicate technical results, and continuously improve validation methodologies, automation, and engineering processes.

Nice to Haves:

• Strong knowledge of AI networking technologies including NCCL, RoCE, and RDMA, with experience debugging both correctness and performance issues at scale.
• Deep understanding of congestion control and lossless Ethernet technologies for AI workloads, including DCQCN, ECN, and PFC.
• Experience debugging issues spanning multiple layers, including networking (L2/L3), transport protocols, operating systems, AI frameworks, and distributed applications.

Perks and Benefits:

• NVIDIA is widely considered to be one of the technology world’s most desirable employers.
• Forward-thinking and hardworking people in the world working for NVIDIA.
• Commitment to fostering a diverse work environment and being an equal opportunity employer.
• Valuing diversity in current and future employees, non-discrimination practices based on various characteristics.